عنوان

Fixed effects regression methods for longitudinal data :

شابک

1590475682

شابک

1590477782

شابک

1629590274

شابک

9781590475683

شابک

9781590477786

شابک

9781629590271

شابک اشتباه

1612909604

شماره

b736349

عنوان اصلي

Fixed effects regression methods for longitudinal data :

نام عام مواد

[Book]

ساير اطلاعات عنواني

using SAS /

نام نخستين پديدآور

Paul D. Allison.

محل نشرو پخش و غیره

Cary, NC :

نام ناشر، پخش کننده و غيره

SAS Institute,

تاریخ نشرو بخش و غیره

2005.

نام خاص و کميت اثر

1 online resource

متن يادداشت

Includes bibliographical references (pages 139-141) and index.

متن يادداشت

Fixed Effects Regression Methods for Longitudinal Data Using SAS, written by Paul Allison, is an invaluable resource for all researchers interested in adding fixed effects regression methods to their tool kit of statistical techniques. First introduced by economists, fixed effects methods are gaining widespread use throughout the social sciences. Designed to eliminate major biases from regression models with multiple observations (usually longitudinal) for each subject (usually a person), fixed effects methods essentially offer control for all stable characteristics of the subjects, even characteristics that are difficult or impossible to measure. This straightforward and thorough text shows you how to estimate fixed effects models with several SAS procedures that are appropriate for different kinds of outcome variables. The theoretical background of each model is explained, and the models are then illustrated with detailed examples using real data. The book contains thorough discussions of the following uses of SAS procedures: PROC GLM for estimating fixed effects linear models for quantitative outcomes, PROC LOGISTIC for estimating fixed effects logistic regression models, PROC PHREG for estimating fixed effects Cox regression models for repeated event data, PROC GENMOD for estimating fixed effects Poisson regression models for count data, and PROC CALIS for estimating fixed effects structural equation models. To gain the most benefit from this book, readers should be familiar with multiple linear regression, have practical experience using multiple regression on real data, and be comfortable interpreting the output from a regression analysis. An understanding of logistic regression and Poisson regression is a plus. Some experience with SAS is helpful, but not required.

منبع سفارش / آدرس اشتراک

Safari Books Online

شماره انبار

CL0500000044

شماره استاندارد بين المللي کتاب و موسيقي

1-59047-568-2

موضوع مستند نشده

SAS (Computer file)

موضوع مستند نشده

SAS (Computer file)

موضوع مستند نشده

SAS (Computer file)

موضوع مستند نشده

Linear models (Statistics)

موضوع مستند نشده

Longitudinal method.

موضوع مستند نشده

Regression analysis.

موضوع مستند نشده

Variables (Mathematics)

موضوع مستند نشده

Linear models (Statistics)

موضوع مستند نشده

Linear models (Statistics)

موضوع مستند نشده

Longitudinal method.

موضوع مستند نشده

Longitudinal method.

موضوع مستند نشده

Mathematical Statistics.

موضوع مستند نشده

MATHEMATICS-- Probability & Statistics-- Regression Analysis.

موضوع مستند نشده

Mathematics.

موضوع مستند نشده

Physical Sciences & Mathematics.

موضوع مستند نشده

Regression analysis.

موضوع مستند نشده

Regression analysis.

موضوع مستند نشده

Variables (Mathematics)

موضوع مستند نشده

Variables (Mathematics)

موضوع مستند نشده

MAT-- 029030

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Allison, Paul David.

تاريخ عمليات

20201203200707.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y